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Privacy-Preserving Power Flow Analysis via secure multi-party computation

IEEE TRANSACTIONS ON SMART GRID 2025年第1期16卷 344-355页

作者： von der Heyden, Jonas Schlueter, Nils Binfet, Philipp Asman, Martin Zdrallek, Markus Jager, Tibor Darup, Moritz Schulze Berg Univ Wuppertal Sch Elect Informat & Media Engn D-42119 Wuppertal Germany Tech Univ Dortmund Dept Mech Engn D-44227 Dortmund Germany

Smart grids feature a bidirectional flow of electricity and data, enhancing flexibility, efficiency, and reliability in increasingly volatile energy grids. However, data from smart meters can reveal sensitive private information. Consequently, the adoption of smart meters is often restricted via legal means and hampered by limited user acceptance. Since metering data is beneficial for fault-free grid operation, power management, and resource allocation, applying privacy-preserving techniques to smart metering data is an important research problem. This work addresses this by using secure multi-party computation (SMPC), allowing multiple parties to jointly evaluate functions of their private inputs without revealing the latter. Concretely, we show how to perform power flow analysis on cryptographically hidden prosumer data. More precisely, we present a tailored solution to the power flow problem building on an SMPC implementation of Newton's method. We analyze the security of our approach in the universal composability framework and provide benchmarks for various grid types, threat models, and solvers. Our results indicate that secure multi-party computation can be able to alleviate privacy issues in smart grids in certain applications.

关键词： Vectors Protocols Smart grids Jacobian matrices Privacy multi-party computation Data aggregation Power system security power distribution cryptography security Newton-Raphson method privacy power flow analysis secure multi-party computation

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A Lightweight CP-ABE Scheme for EHR Over Cloud Based on Blockchain and secure multi-party computation

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2025年第2期36卷

作者： Qiao, Jiawen Wang, Na Fu, Junsong Deng, Lunzhi Wang, Jingjing Liu, Jianwei Beihang Univ Sch Cyber Sci & Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing Peoples R China Guizhou Normal Univ Sch Math Sci Guiyang Peoples R China

With the growth of cloud computing and the popularity of electronic health records (EHR), more and more patients and hospitals are uploading EHR to the cloud for storage, retrieval and organization. Due to the privacy of EHR, cloud-based EHR systems need to protect data security and provide access control, and attribute-based encryption (ABE) is the appropriate technology. Nevertheless, traditional single-center ABE schemes do not conform to the collaborative scenario of electronic health care, and some of them do not support real-time attribute update. Consequently, this paper proposes a lightweight CP-ABE scheme for EHR over cloud based on blockchain and secure multi-party computation (LCBS). First, we introduce the model of multi-authority and innovatively apply secure multi-party computation to initialize the system, which maintains normal system operation while the power is decentralized. Second, we deploy a blockchain suitable for EHR systems to record the users' key information, assisting multiple entities to verify the key at different stages and protecting the EHR from illegal acquisition. In addition, our scheme supports lightweight attribute update, which requires small amount of computational overhead to achieve instant attribute update. Finally, through formal security analysis and simulation experiments of the LCBS system, it is shown that our scheme guarantees data security and improves computing efficiency.

关键词： blockchain CP-ABE electronic health record secret sharing secure multi-party computation

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Challenges and future research directions in secure multi-party computation for resource-constrained devices and large-scale computations

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INTERNATIONAL JOURNAL OF INFORMATION SECURITY 2025年第1期24卷 1-29页

作者： Gamiz, Idoia Regueiro, Cristina Lage, Oscar Jacob, Eduardo Astorga, Jasone Univ Basque Country UPV EHU Dept Commun Engn Bilbao 48013 Bizkaia Spain TECNALIA BRTA Bizkaia Sci & Technol Pk 700 Derio 48160 Bizkaia Spain

In the era of Big Data and the advancement of the Internet of Things, there is an increasing amount of valuable information. It is important to emphasize that this data is usually sensitive or confidential, so security and privacy are two of the highest priorities for organizations when performing Data Mining. Researchers have explored techniques such as secure multi-party computation (SMPC) in the last decades. Nevertheless, there is still a significant gap between the theory of SMPC and its applicability, especially when working with resource-constrained devices or massive data. This work has been conducted with a systematic literature review, and it intends to analyze the open issues of adapting SMPC to those scenarios, by classifying the studies to answer two research questions: (1) how has the use of SMPC attempted to be adapted to constrained devices? and (2) how have traditional techniques fitted with Big Data? At the end of the process, after analyzing a total of 637 studies, 19 papers were selected. Regarding constrained devices, solutions are grouped into three main techniques: secure outsourcing, hardware-based trusted execution, and intermediate representations. As for Big Data, the selected studies use mixed protocols to change over cleartext and ciphertext, combine different types of SMPC protocols, or modify existing protocols through optimizations.

关键词： secure multi-party computation Privacy-preserving computing Privacy Constrained devices Big data IoT

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secure multi-party computation without agreement

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JOURNAL OF CRYPTOLOGY 2005年第3期18卷 247-287页

作者： Goldwasser, S Lindell, Y Weizmann Inst Sci Dept Comp Sci IL-76100 Rehovot Israel Bar Ilan Univ Dept Comp Sci IL-52900 Ramat Gan Israel

It has recently been shown that authenticated Byzantine agreement, in which more than a third of the parties are corrupted, cannot be securely realized under concurrent or parallel (stateless) composition. This result puts into question any usage of authenticated Byzantine agreement in a setting where many executions take place. In particular, this is true for the whole body of work of secure multi-party protocols in the case that a third or more of the parties are corrupted. This is because these protocols strongly rely on the extensive use of a broadcast channel, which is in turn realized using authenticated Byzantine agreement. We remark that it was accepted folklore that the use of a broadcast channel (or authenticated Byzantine agreement) is actually essential for achieving meaningful secure multi-party computation whenever a third or more of the parties are corrupted. In this paper we show that this folklore is false. We present a mild relaxation of the definition of secure computation allowing abort. Our new definition captures all the central security issues of secure computation, including privacy, correctness and independence of inputs. However, the novelty of the definition is in decoupling the issue of agreement from these issues. We then show that this relaxation suffices for achieving secure computation in a point-to-point network. That is, we show that secure multi-party computation for this definition can be achieved for any number of corrupted parties and without a broadcast channel (or trusted pre-processing phase as required for running authenticated Byzantine agreement). Furthermore, this is achieved by just replacing the broadcast channel in known protocols with a very simple and efficient echo-broadcast protocol. An important corollary of our result is the ability to obtain multi-party protocols that remain secure under composition, without assuming a broadcast channel.

关键词： secure multi-party computation broadcast protocol composition

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secure multi-party computation: Theory, practice and applications

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INFORMATION SCIENCES 2019年 476卷 357-372页

作者： Zhao, Chuan Zhao, Shengnan Zhao, Minghao Chen, Zhenxiang Gao, Chong-Zhi Li, Hongwei Tan, Yu-an Univ Jinan Shandong Prov Key Lab Network Based Intelligent C Jinan 250022 Shandong Peoples R China Univ Jinan Sch Informat Sci & Engn Jinan 250022 Shandong Peoples R China Shandong Univ Sch Comp Sci & Technol Jinan Shandong Peoples R China Tsinghua Univ Sch Software Beijing Peoples R China Guangzhou Univ Sch Comp Sci Guangzhou Guangdong Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Ctr Cyber Secur Chengdu Sichuan Peoples R China Beijing Inst Technol Sch Comp Sci Beijing Peoples R China

secure multi-party computation (SMPC) is a generic cryptographic primitive that enables distributed parties to jointly compute an arbitrary functionality without revealing their own private inputs and outputs. Since Yao's seminal work in 1982, 30 years of research on SMPC has been conducted, proceeding from pure theoretical research into real-world applications. Recently, the increasing prevalence of the newly emerging technologies such as cloud computing, mobile computing and the Internet of Thing has resulted in a re-birth of SMPC's popularity. This has occurred mainly because, as a generic tool for computing on private data, SMPC has a natural advantage in solving security and privacy issues in these areas. Accordingly, many application-oriented SMPC protocols have been constructed. This paper presents a comprehensive survey on the theoretical and practical aspects of SMPC protocols. Specifically, we start by demonstrating the underlying concepts of SMPC, including its security requirements and basic construction techniques. Then, we present the research advances regarding construction techniques for generic SMPC protocols, and also the cutting-edge approaches to cloud-assisted SMPC protocols. Then, we summarize the concrete application-oriented protocols that are currently available, and finally, we present a discussion of the current literature and conclude this survey. (C) 2018 Elsevier Inc. All rights reserved.

关键词： secure multi-party computation Generic protocol Cloud security secure outsourcing Privacy-preserving technology

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secure multi-party computation for Personalized Human Activity Recognition

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NEURAL PROCESSING LETTERS 2023年第3期55卷 2127-2153页

作者： Melanson, David Maia, Ricardo Kim, Hee-Seok Nascimento, Anderson De Cock, Martine Univ Washington Sch Engn & Technol 1900 Commerce St Tacoma WA 98402 USA Univ Brasilia Inst Exact Sci Dept Comp Sci BR-70910900 Brasilia DF Brazil Univ Ghent Dept Appl Math Comp Sci & Stat Krijgslaan 281 S9 B-9000 Ghent Belgium

Calibrating Human Activity Recognition (HAR) models to end-users with Transfer Learning (TL) often yields significant accuracy improvements. Such TL is by design done based on very personal data collected by sensors worn close to the human body. To protect the users' privacy, we therefore introduce secure multi-party computation (MPC) protocols for personalization of HAR models, and for secure activity recognition with the personalized models. Our MPC protocols do not require the end-users to reveal their sensitive data in an unencrypted manner, nor do they require the application developer to disclose their trained model parameters or any other sensitive or proprietary information with anyone in plaintext. Through experiments on HAR benchmark datasets, we demonstrate that our privacy-preserving solution yields the same accuracy gains as TL in-the-clear, i.e. when no measures to protect privacy are in place, and that our approach is fast enough for use in practice.

关键词： Transfer learning Human activity recognition Convolutional neural network secure multi-party computation Cryptography Privacy

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secure multi-party computation with secret sharing for real-time data aggregation in IIoT

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COMPUTER COMMUNICATIONS 2024年 224卷 159-168页

作者： Liu, Dengzhi Yu, Geng Zhong, Zhaoman Song, Yuanzhao Jiangsu Ocean Univ Sch Comp Engn Lianyungang 210005 Peoples R China Jiangsu Inst Marine Resources Dev Lianyungang 210005 Peoples R China Jiangsu Ocean Univ Jiangsu Engn Res Ctr Intelligent Port Lianyungang 210005 Peoples R China Gachon Univ Dept Business Seongnam 13120 Gyeonggi Do South Korea

Real-time analytics in Industrial Internet-of-Things (IIoT) has received remarkable attention recently due to its capacity to prevent downtime and manage risks. However, the sensed data in IIoT is considered private. Thus, the sensed data of IIoT nodes cannot be transmitted and utilized directly in the cloud server due to the risk of privacy leakage. Data aggregation can effectively balance the availability of data with privacy concerns, making it particularly well-suited for IIoT systems. Although several privacy-preserving aggregation schemes in IIoT have been proposed, the majority of them can only support a single type of aggregation that limits the application scenarios of data aggregation. To address the problems mentioned above, a real-time aggregation analysis scheme for IIoT is proposed, which is constructed based on secure multi-party computation with secret sharing. Specifically, the multi-party computation with secret sharing is utilized to implement data aggregation process for IIoT that achieves multiple types of data aggregation. In addition, the secret sharing is utilized in the proposed scheme that can significantly improve the efficiency of the proposed scheme compared with similar schemes. Moreover, the proposed scheme does not require the involvement of a trusted authority in the data aggregation. Security and performance analyses show that the proposed scheme can enhance the security of the sensed data while effectively aggregating data for real-time analytics in IIoT.

关键词： Real-time analytics IIoT Data aggregation secure multi-party computation Secret sharing

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secure multi-party computation solution to Yao's millionaires' problem based on set-inclusion

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Progress in Natural Science:Materials International 2005年第9期15卷 851-856页

作者： LI Shundong**, DAI Yiqi and YOU Qiyou(Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China) Department of Computer Science and Technology Tsinghua University Beijing 100084 China

secure multi-party computation is a focus of international cryptography in recent years. Protocols for Yao’s millionaires’ problem have become an important building block of many secure multi-party computation protocols. Their efficiency are crucial to the efficiency of many secure multi-party computation protocols. Unfortunately, known protocols for Yao’s millionaires’ problem have high computational complexity or communication complexity. In this study, based on the 1-out-of-m oblivious transfer and set-inclusion problem, we propose a new protocol to solve this problem. This new protocol is very efficient in terms of both computational and communication complexities. Its privacy-preserving property is also proved by simulation paradigm which is generally accepted in the study of secure multi-party computation. We also compare the information leakage of our new protocol and the known protocols.

关键词： secure multi-party computation Yao’s millionaires’ problem 1-out-of-m oblivious transfer set-inclusion problem.

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secure multi-party computation made simple

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DISCRETE APPLIED MATHEMATICS 2006年第2期154卷 370-381页

作者： Maurer, U ETH Dept Comp Sci CH-8092 Zurich Switzerland

Known secure multi-party computation protocols are quite complex, involving non-trivial mathematical structures and sub-protocols. The purpose of this paper is to present a very simple approach to secure multi-party computation with straight-forward security proofs. This approach naturally yields protocols secure for mixed (active and passive) Corruption and general (as opposed to threshold) adversary structures, confirming the previously proved tight bounds in a simpler framework. Due to their simplicity, the described protocols are well-suited for didactic purposes, which is a main goal of this paper. (c) 2005 Elsevier B.V. All rights reserved.

关键词： secure multi-party computation verifyable secret sharing adversary structures

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secure multi-party computation protocol for sequencing problem

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Science China(Information Sciences) 2011年第8期54卷 1654-1662页

作者： TANG ChunMing 1,2,SHI GuiHua 1 & YAO ZhengAn 3 1 School of Mathematics and Information Science,Guangzhou University,Guangzhou 510006, China 2State Key Laboratory of Information Security, Institute of Software Science,Chinese Academy of Sciences,Beijing 100080,China 3 School of Mathematics and computational Science,Sun Yat-Sen University,Guangzhou 510275,China School of Mathematics and Information Science Guangzhou University Guangzhou China State Key Laboratory of Information Security Institute of Software Science Chinese Academy of Sciences Beijing China School of Mathematics and Computational Science Sun Yat-Sen University Guangzhou China

In the field of multi-party computation,an important problem is how to construct an efficient and secure multi-party computation protocol for certain specific *** the present study,we make use of a secret sharing scheme to construct an efficient and secure multi-party computation protocol for sequencing *** protocols are perfectly secure against both a passive adversary that can corrupt at most t (n-1)/2 participants, and an active adversary that can corrupt at most t < n/3 *** simplest sequencing problem is the Millionaires' problem.

关键词： secure multi-party computation sequencing problem secret sharing

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